Image recognition system and recognition method thereof, and program
A task is to correctly classify an input image regardless of a fluctuation in illumination and a state of occlusion of the input image. Input image sub-region extraction means 2 extracts a sub-region of the input image. Inter-pattern distance calculation means 3 calculates an inter-pattern distance between this sub-region and a sub-region of a registration image pre-filed in dictionary filing means 5 for each sub-region. Region distance value integration means 10 integrates the inter-pattern distances obtained for each sub-region. This is conducted for the registration image of each category. Identification means 4 finds a minimum value out of its integrated inter-pattern distances, and in the event that its minimum value is smaller than a threshold, outputs a category having its minimum distance as a recognition result.
1. An image recognition system comprising:
inter-pattern distance calculation means for calculating inter-pattern distances between an input image and registration images on each sub-region of a plurality of sub-regions;
inter-pattern distance integration means for selecting a portion of said plurality of sub-regions in an ascending order of said inter-pattern distances and integrating said inter-pattern distances of said selected sub-regions into an integrated inter-pattern distance; and
identification means for identifying said registration image with minimum integrated inter-pattern distance.
2. An image recognition system comprising:
fluctuation image generation means for converting a registration image into a plurality of registration images, each of the plurality of registration images differing in visualization due to a variation in posture and a variation in illumination;
subspace distance calculation means for calculating subspace distance values between each of a plurality of sub-regions of an input image, and a plurality of sub spaces of sub-regions of said registration images; and
identification means for identifying said input image based on said subspace distance values.
3. An image recognition system comprising:
inter-subspace distance calculation means for calculating, sub-region by sub-region, inter-subspace distance values between each of a plurality of subspaces of sub-regions of an input image that is comprised of a plurality of images, and each of a plurality of subspaces of sub-regions of registration images that are comprised of a plurality of images, the plurality of sub-regions of the registration images corresponding to said plurality of sub-regions of said input image; and
identification means for identifying said input image based on said inter-subspace distance values.
4. The image recognition system as set forth in claim 3 , wherein said inter-subspace distance calculation means calculates the inter-subspace distance values between a subspace formed by K vectors that is generated from said sub-regions of said registration images, and a subspace formed by L vectors that is generated from said sub-regions of said input images.
5. An image recognition system comprising;
a first fluctuation image generation means for converting a registration image into a plurality of registration images, each differing in visualization due to a variation in posture or a variation in illumination;
a second fluctuation image generation means for converting an input image into a plurality of input images, each differing in visualization due to a variation in posture and a variation in illumination;
inter-subspace distance calculation means for calculating inter-subspace distance values between each of a plurality of sub-regions of said input images, and a plurality of sub-regions of said registration images that correspond to said sub-regions of said input images; and
identification means for identifying said input image based on said inter-subspace distance values.
6. The image recognition system as set forth in claim 5 , wherein said inter-subspace distance calculation means calculates the inter-subspace distance values between a subspace formed by K vectors that is generated from said sub-regions of said registration images, and a subspace formed by L vectors that is generated from said sub-regions of said input images.
7. An image recognition method comprising using a computer to carry out the steps of:
calculating inter-pattern distance between an input image and registration images on each sub-region of a plurality of sub-regions;
integrating said inter-pattern distances for selecting a portion of said plurality of sub-regions in an ascending order of said inter-pattern distances and integrating said inter-pattern distances of said selected sub-regions into an integrated inter-pattern distance; and
identifying said registration image with minimum integrated inter-pattern distance.
8. An image recognition method comprising using a computer to carry out the steps of: converting a registration image into a plurality of registration images, each of the plurality of registration images differing in visualization due to a variation in posture and a variation in illumination;
calculating subspace distance values between each of a plurality of sub-regions of an input image, and a plurality of subspaces of sub-regions of said registration images; and
identifying said input image based on said subspace distance values.
9. An image recognition method comprising using a computer to carry out the steps of:
calculating, sub-region by sub-region, inter-subspace distance values between each of a plurality of subspaces of sub-regions of an input image that is comprised of a plurality of images, and each of a plurality of subspaces of sub-regions of registration images that are comprised of a plurality of images, the plurality of sub-regions of the registration images corresponding to said plurality of sub-regions of said input image; and
identifying said input image based on said inter-subspace distance values.
10. The image recognition method as set forth in claim 9 , wherein said calculating the inter-subspace distance values comprises calculating the inter-subspace distance values between a subspace formed by K vectors that is generated from said sub-regions of said registration images, and a subspace formed by L vectors that is generated from said sub-regions of said input images.
11. An image recognition method comprising using a computer to carry out the steps of:
converting a registration image into a plurality of registration images, each differing in visualization due to a variation in posture or a variation in illumination;
converting an input image into a plurality of input images, each differing in visualization due to a variation in posture and a variation in illumination;
calculating inter-subspace distance values between each of a plurality of sub-regions of said input images, and a plurality of sub-regions of said registration images that correspond to said sub-regions of said input images; and
identifying said input image based on said inter-subspace distance values.
12. The image recognition method as set forth in claim 11 , wherein said calculating the inter-subspace distance values comprises calculating the inter-subspace distance values between a subspace formed by K vectors that is generated from said sub-regions of said registration images, and a subspace formed by L vectors that is generated from said sub-regions of said input images.
13. A computer readable storage medium storing a program for executing an image recognition method, the method comprising:
calculating inter-pattern distance between an input image and registration images on each sub-region of a plurality of sub-regions;
integrating said inter-pattern distances for selecting a portion of said plurality of sub-regions in an ascending order of said inter-pattern distances and integrating said inter-pattern distances of said selected sub-regions into an integrated inter-pattern distance; and
identifying said registration image with minimum integrated inter-pattern distance.
14. A computer readable storage medium storing a program for executing an image recognition method, the method comprising:
converting a registration image into a plurality of registration images, each of the plurality of registration images differing in visualization due to a variation in posture and a variation in illumination;
calculating subspace distance values between each of a plurality of sub-regions of an input image, and a plurality of subspaces of sub-regions of said registration images; and identifying said input image based on said subspace distance values.
15. A computer readable storage medium storing a program for executing an image recognition method, the method comprising:
calculating, sub-region by sub-region, inter-subspace distance values between each of a plurality of subspaces of sub-regions of an input image that is comprised of a plurality of images, and each of a plurality of subspaces of sub-regions of registration images that are comprised of a plurality of images, the plurality of sub-regions of the registration images corresponding to said plurality of sub-regions of said input image; and
identifying said input image based on said inter-subspace distance values.
16. The computer readable storage medium as set forth in claim 15 , wherein said calculating the inter-subspace distance values comprises calculating the inter-subspace distance values between a subspace formed by K vectors that is generated from said sub-regions of said registration images, and a subspace formed by L vectors that is generated from said sub-regions of said input images.
17. A computer readable storage medium storing a program for executing an image recognition method, the method comprising;
converting a registration image into a plurality of registration images, each differing in visualization due to a variation in posture and a variation in illumination;
converting an input image into a plurality of input images, each differing in visualization due to a variation in posture or a variation in illumination;
calculating inter-subspace distance values between each of a plurality of sub-regions of said input images, and a plurality of sub-regions of said registration images that correspond to said sub-regions of said input images; and
identifying said input image based on said inter-subspace distance values.
18. The computer readable storage medium as set forth in claim 17 , wherein said calculating the inter-subspace distance values comprises calculating the inter-subspace distance values between a subspace formed by K vectors that is generated from said sub-regions of said registration images, and a subspace formed by L vectors that is generated from said sub-regions of said input images.
19. An image recognition system comprising: fluctuation image generation means for converting a registration image into a plurality of registration images, each of the plurality of registration images differing in visualization due to a variation in posture or a variation in illumination;
subspace distance calculation means for calculating subspace distance values between each of a plurality of sub-regions of an input image, and a plurality of subspaces of sub-regions of said registration images; and
identification means for identifying said input image based on said subspace distance values.
20. An image recognition method comprising using a computer to carry out the steps of:
converting a registration image into a plurality of registration images, each of the plurality of registration images differing in visualization due to a variation in posture or a variation in illumination;
calculating subspace distance values between each of a plurality of sub-regions of an input image, and a plurality of subspaces of sub-regions of said registration images; and
identifying said input image based on said subspace distance values.
21. A computer readable storage medium storing a program for executing an image recognition method, the method comprising:
converting a registration image into a plurality of registration images, each of the plurality of registration images differing in visualization due to a variation in posture or a variation in illumination;
calculating subspace distance values between each of a plurality of sub-regions of an input image, and a plurality of subspaces of sub-regions of said registration images; and
identifying said input image based on said subspace distance values.